Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 1998. / Includes bibliographical references.

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 56-59). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 63-66). Also available in electronic version. Access restricted to campus users.

This thesis addresses the capital replacement modelling problems associated with a mixed, or inhomogeneous, fleet and also takes account of the fleet size problem. Applications considered relate to a fleet of buses and a fleet of medical equipment. The initial chapters introduce the notion of capital replacement modelling and review previous work in the field, as well as reviewing the fleet size problem. Replacement policies are also put in the context of the fleet rather than the context of a 'typical plant'. In the third chapter, we present our first attempt to model capital replacement with variable fleet size over a finite planning horizon. A two cycle model is developed in which the notion of penalty cost for breakdown is introduced. This cost is incurred when demand is not met. To take account of the cost of unmet demand, a simple failure model for plant is proposed. The replacement model is applied to a fleet of ventilators in an intensive care unit of a hospital. In the fourth chapter we develop various models for the case of replacement of a sub-fleet within a mixed fleet. These models themselves have variable finite planning horizon of variable length and build on developments described earlier in the thesis. Other aspects such as the increased cost of sub-optimal policy due to delayed replacement, smaller replacement sub-fleet etc. are also considered. The models developed in chapter 4 are applied, in the following chapter, to a fleet of buses operated by a Malaysian inter-city bus company. Sensitivity analysis on different factors is also carried out. Finally the sensitivity of optimal decision policy to the choice of the replacement model is described in the context of the bus application.

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005

Thesis (M.S.)--Oregon State University, 2009. / Printout. Includes bibliographical references (leaves 58-59). Also available on the World Wide Web.

D.Comm. / In Chapter 1 events relating to government motor transport in South Africa were discussed. It became clear that there was uncertainty regarding the best way forward for government motor transport. Conflicting information as to which was the best model emanated from institutions outside Gauteng: some institutions were outsourcing their fleets, whilst others were decentralising their fleets to user departments. In some cases there was a movement from a decentralised to a centralised system. All the above led to the question whether there was a better way of managing government motor transport and of making strategic decisions such as outsourcing or decentralising the fleet. It was stated in Chapter 1 that the approach to fleet management in Gauteng was not an all-encompassing process, thus giving rise to suboptimal decisions. In particular, problems had to be solved without the all-inclusive and focused management information that is needed to make informed decisions. Contradicting signals from institutions that operate government-owned fleets throughout South Africa further complicated the situation. This was causing further uncertainty as to the way forward. There was a need for a decision-making process and tool that takes into account the broader picture, including the interest of all important stakeholders. The chapter then highlighted the need to provide an overall strategic framework within which more informed decisions could be made. This would reduce uncertainty and provide a solid base from where government motor transport could be managed and developed. / Prof. G.C. Walters